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White Paper

Humility in AI: Building Trustworthy and Ethical AI Systems

AI is becoming ubiquitous. More and more critical decisions are automated through machine learning models, determining the future of a business or making life-altering decisions for real people. The number of critical touch points is growing exponentially with the adoption of AI.

But with the incredible pace of the modern world, AI systems continually face new data patterns, which make it challenging to return reliable predictions. This could mean a catastrophic failure by the system down the line, especially without proper guardrails. These failures can also significantly erode human trust in AI, rendering it ineffective for real-world applications in many industries.

With the rising stakes, AI systems must be built to be humble, just like humans. AI should know when it is not sure about the right answer to transfer the critical decision-making process back to people.

In this ebook, we explore the concept of humility in AI systems and how it can be applied to existing solutions to ensure their trustworthiness, ethicality, and reliability in a fast-changing world.

Download this ebook to learn:

  • The basic concepts behind humility in AI
  • What makes AI systems susceptible to performance and accuracy issues
  • How AI systems can exhibit humility
  • What it takes to develop a systemic, qualified, and actionable understanding of the potential areas for weakness in AI systems
  • How humility in AI systems impacts their decisions
  • Real-life examples of business problems and issues with the underlying data used for predictions that may benefit from a humility framework
  • How humble AI system can improve tactical and strategic decisions
  • What actions an automated system should perform when it’s not sure about its predictive output
  • How DataRobot tackles predictive uncertainty with its Humble AI capability
DataRobot is an indispensable partner helping us maintain our reputation both internally and externally by deploying, monitoring, and governing generative AI responsibly and effectively.
Tom Thomas
Tom Thomas

Vice President of Data & Analytics, FordDirect

The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards. We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence
Rosalia Tungaraza
Rosalia Tungaraza

Ph.D, AVP, Artificial Intelligence, Baptist Health

DataRobot provides us with innovative ways to test new ideas. Given a problem and a dataset, DataRobot allows us to generate multiple prototypes 20% faster. And the process facilitates the learning evolution of our data scientists.
Diego J. Bodas
Diego J. Bodas

Director of Advanced Analytics, MAPFRE ESPAÑA

The value of having a single platform that pulls all the components together can’t be underestimated. Then there’s the combination of the technology and the collaborative DataRobot team. If either one of those wasn’t there, I would have looked elsewhere.
Craig Civil
Craig Civil

Director of Data Science & AI

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